Resumen
Antecedentes: el objetivo del presente estudio es doble: (1) analizar y validar la estructura factorial de las escalas del Miedo al COVID-19, Capacitación en seguridad y salud en el lugar de trabajo, y el Cumplimiento de seguridad conductual (Estudio 1) en trabajadores españoles de primera línea de COVID-19 de diferentes sectores (sector alimentario, hospitales y servicios asistenciales de defunciones); y (2) analizar y validar la estructura factorial de una versión reducida de dichas escalas (Estudio 2) en trabajadores españoles del sector sanitario. Método: los análisis realizados con el programa R 1.4.2. permiten validar la estructura factorial de las escalas en los dos estudios realizados. La muestra estuvo compuesta por 361 participantes en el estudio 1; y 708 participantes en el estudio 2. Resultados: los resultados indican que los instrumentos ofrecen una evidencia adecuada de fiabilidad y validez. Conclusiones: el cuestionario (especialmente la versión corta) puede ser utilizado por empleados/as de primera línea de COVID-19 de manera confiable y válida en periodo post-COVID-19 e incluso para prevenir potenciales eventos similares futuros que amenacen potencialmente la salud física y mental de los y las profesionales.
Citas
Ahorsu, D. K., Lin, C. Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2020). The fear of COVID-19 scale: Development and initial validation. International Journal of Mental Health and Addiction, 20, 1537-1545. https://doi.org/10.1007/s11469-020-00270-8
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238-246. https://psycnet.apa.org/doi/10.1037/0033-2909.107.2.238
Billings, J., Ching, B. C. F., Gkofa, V., Greene, T., & Bloomfield, M. (2021). Experiences of frontline healthcare workers and their views about support during COVID-19 and previous pandemics: A systematic review and qualitative meta-synthesis. BMC Health Services Research, 21, Article 923. https://doi.org/10.1186/s12913-021-06917-z
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing Structural Equation Models (pp. 136-62). Sage.
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233-255. https://doi.org/10.1207/S15328007SEM0902_5
Chi, H., Vu, T.V., Vo-Thanh, T., Nguyen, N.P., Van Nguyen, D. (2020). Workplace health and safety training, employees’ risk perceptions, behavioral safety compliance, and perceived job insecurity during COVID-19: data of Vietnam. Data in Brief, 33, Article 106346. https://doi.org/10.1016/J.DIB.2020.106346
Cho, S. J., Lee, J. Y., & Winters, J. V. (2020). COVID-19 employment status impacts on food sector workers. IZA Institute of Labor Economics, Article 13334. http://dx.doi.org/10.2139/ssrn.3627034
Cirrincione, L., Plescia, F., Ledda, C., Rapisarda, V., Martorana, D., Moldovan,
R. E., Theodoridou, K., & Cannizzaro, E. (2020). COVID-19 Pandemic: Prevention and protection measures to be adopted at the workplace. Sustainability, 12(9), Article 3603. https://doi.org/10.3390/SU12093603
De Angelis, M., Giusino, D., Nielsen, K., Aboagye, E., Christensen, M., Innstrand, S. T., ... & Pietrantoni, L. (2020). H-work project: Multilevel interventions to promote mental health in SMEs and public workplaces. International Journal of Environmental Research and Public Health, 17(21), Article 8035. https://doi.org/10.3390/ijerph17218035
DiStefano, C., & Morgan, G. B. (2014). A comparison of diagonal weighted least squares robust estimation techniques for ordinal data. Structural Equation Modeling: A Multidisciplinary Journal, 21(3), 425-438. https://doi.org/10.1080/10705511.2014.915373
Dumont, C., & Babykina, G. (2022). The impacts of COVID-19 pandemic on the food sector and on supermarket employees in France during the first Lockdown period. Healthcare, 10(8), Article 1404. https://doi.org/10.3390/ healthcare10081404
Frenkel, M. O., Giessing, L., Egger-Lampl, S., Hutter, V., Oudejans, R. R. D., Kleygrewe, L., Jaspaert, E., & Plessner, H. (2021). The impact of the COVID-19 pandemic on european police officers: Stress, demands, and coping resources. Journal of Criminal Justice, 72, Article 101756. https://doi.org/10.1016/J.JCRIMJUS.2020.101756
Fusar-Poli, P., Brambilla, P., & Solmi, M. (2020). Learning from COVID-19 pandemic in northen Italy: Impact on mental health and clinical care. Journal of Affective Disorders, 275, 78–79. https://doi.org/10.1016/j. jad.2020.06.028
García-Fernández, L., Romero-Ferreiro, V., López-Roldán, P. D., Padilla, S., Calero-Sierra, I., Monzó-García, M., ... Rodriguez-Jimenez, R. (2022). Mental health impact of COVID-19 pandemic on Spanish healthcare workers. Psychological Medicine, 52(1), 195-197. https://doi.org/10.1017/S0033291720002019
Gil-Beltrán, E., Llorens, S., & Salanova, M. (2020). Employees physical exercise, resources, engagement, and performance: A cross-sectional study from HERO Model. Revista de Psicología del Trabajo y de las Organizaciones, 36(1), 39-47. https://doi.org/10.5093/jwop2020a4
Gómez-Galán, J., Lázaro-Pérez, C., Martínez-López, J. Á., & Fernández- Martínez, M. D. M. (2020). Burnout in Spanish security forces during the covid-19 pandemic. International Journal of Environmental Research and Public Health, 17(23), 1–15. https://doi.org/10.3390/ ijerph17238790
Guadagnoli, E., & Velicer, W. F. (1988). Relation of sample size to the stability of component patterns. Psychological Bulletin, 103(2), 265-275. https://doi.org/10.1037/0033-2909.103.2.265
Hair, J., Black, W., Babin, B., & Anderson, R. (2010). Multivariate data analysis (7th ed.). Prentice-Hall.
Hu, L. T., & Bentler, P. M. (1999). Cut off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: a Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
Koontalay, A., Suksatan, W., Prabsangob, K., & Sadang, J. M. (2021). Healthcare workers’ burdens during the COVID-19 pandemic: A qualitative systematic review. Journal of Multidisciplinary Healthcare, 14, 3015-3025. https://doi.org/10.2147/JMDH.S330041
Lin, C. Y., Broström, A., Griffiths, M. D., & Pakpour, A. H. (2020). Investigating mediated effects of fear of COVID-19 and COVID-19 misunderstanding in the association between problematic social media use, psychological distress, and insomnia. Internet Interventions, 21, Article 100345. https://doi.org/10.1016/j.invent.2020.100345
Marcomini, I., Agus, C., Milani, L., Sfogliarini, R., Bona, A., & Castagna, M. (2021). COVID-19 and post-traumatic stress disorder among nurses: A descriptive cross-sectional study in a COVID hospital. La Medicina del Lavoro, 112(3), 241–249. https://doi.org/10.23749/mdl.v112i3.11129
McLean, L., Bryce, C., & Johnson, B. (2023). Describing Teachers’Well-Being Prior to and 18 Months After COVID-19 School Closures, with a Focus on Early-Career Teachers and Teachers of Color. Sage Open, 13(4). https://doi.org/10.1177/21582440231217872
Nielsen, K., & Christensen, M. (2021). Positive participatory organizational interventions: A multilevel approach for creating healthy workplaces. Frontiers in Psychology, 12, Article 696245. https://doi.org/10.3389/ fpsyg.2021.696245
Pappas, G., Kiriaze, I. J., Giannakis, P., & Falagas, M. E. (2009). Psychosocial consequences of infectious diseases. Clinical Microbiology and Infection, 15(8), 743-747. https://doi.org/10.1111/j.1469-0691.2009.02947.x
Puth, M.-T., Neuhäuser, M., & Ruxton, G. D. (2015). Effective use of Spearman’s and Kendall’s correlation coefficients for association between two measured traits. Animal Behaviour, 102, 77-84. https://doi. org/10.1016/j.anbehav.2015.01.010
Qiu, J., Shen, B., Zhao, M., Wang, Z., Xie, B., & Xu, Y. (2020). A nationwide survey of psychological distress among Chinese people in the COVID-19 epidemic: implications and policy recommendations. General Psychiatry, 33, Article 100213. https://doi.org/10.1136/gpsych-2020-100213
R Core Team (2022). R: A language and environment for statistical computing.
R Foundation for Statistical Computing. https://www.R-project.org/
Revelle, W. (2022). psych: Procedures for psychological, psychometric, and personality Research. Northwestern University, Evanston, Illinois. R package version 2.2.9, https://CRAN.R-project.org/package=psych.
Ropeik, D. (2004). The consequences of fear. EMBO Reports, 5, 56-60. Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/ jss.v048.i02
Salanova, M., Llorens, S., Cifre, E., & Martínez, I. M. (2012). We need a hero! Toward a validation of the healthy and resilient organization (HERO) model. Group and Organization Management, 37(6), 785–822. https://doi.org/10.1177/1059601112470405
Salanova, M., Llorens, S., & Martínez, I. M. (2019). Organizaciones saludables. Una mirada desde la psicología positiva (1ª ed.) [Healthy organizations. A look from Positive Psychology]. Aranzadi.
Salanova, M. & Soler, C. (2020). Cultivando organizaciones saludables y resilientes: Metodología HERO en la prevención de riesgos psicosociales [Cultivating healthy and resilient organizations: HERO methodology in the prevention of psychosocial risks]. In A. L. García- Izquierdo (Ed.) Intervención psicosocial para una prevención de riesgos laborales inclusiva [Psychosocial intervention to an inclussive job risks prevention] (pp. 53-76). Cátedra Asturias Prevención.
Sanford, J., Agrawal, A., & Miotto, K. (2021). Psychological distress among women healthcare workers: A health System’s experience developing emotional support services during the COVID-19 pandemic. Frontiers in Global Women’s Health, 2, Article 614723. https://doi.org/10.3389/ fgwh.2021.614723
Sakib, N., Akter, T., Zohra, F., Bhuiyan, A. K. M. I., Mamun, M. A., & Griffiths, M. D. (2021). Fear of COVID-19 and depression: A comparative study among the general population and healthcare professionals during COVID-19 pandemic crisis in Bangladesh. International Journal of Mental Health and Addiction, 21, 976-992. https://doi.org/10.1007/s11469-020-00477-9
Shrestha, N. (2021). Factor analysis as a tool for survey analysis. American Journal of Applied Mathematics and Statistics, 9(1), 4-11. https://doi.org/10.12691/ajams-9-1-2
Smith, M. A., & Leigh, B. (1997). Virtual subjects: Using the internet as an alternative source of subjects and research environment. Behavior Research Methods, Instruments, & Computers, 29, 496-505. https://doi.org/10.3758/ BF03210601
Stogner, J., Miller, B. L., & McLean, K. (2020). Police Stress, mental health, and resiliency during the COVID-19 pandemic. American Journal of Criminal Justice, 45(4), 718–730. https://doi.org/10.1007/s12103-020-09548-y
Streiner, D. L. (2003). Starting at the beginning: an introduction to coefficient alpha and internal consistency. Journal of Personality Assessment, 80(1), 99-103. https://doi.org/10.1207/S15327752JPA8001_18
Yıldırım, M., & Solmaz, F. (2022). COVID-19 burnout, COVID-19 stress and resilience: Initial psychometric properties of COVID-19 burnout Scale. Death Studies, 46(3), 524–532. https://doi.org/10.1080/07481187.2020.1818885
Zhang, W. R., Wang, K., Yin, L., Zhao, W. F., Xue, Q., Peng, M., Min, B. Q., Tian, Q., Leng, H. X., Du, J. L., Chang, H., Yang, Y., Li, W., Shangguan,
F. F., Yan, T. Y., Dong, H. Q., Han, Y., Wang, Y. P., Cosci, F., & Wang, H. X. (2020). Mental health and psychosocial problems of medical health workers during the COVID-19 epidemic in China. Psychotherapy and Psychosomatics, 89(4), 242–250. https://doi.org/10.1159/000507639